DataStax Enterprise

What do you like best about the product?

AstraDB's Vector Search capabilities and the simple GUI interface of Langflow.
Langflow made it easier to implement and effortlessly integrate the solution into the entire process flow.

What do you dislike about the product?

It is a little pricey but it delivers on the promise of seamless and effortless integration

What problems is the product solving and how is that benefiting you?

RAG search is common but highly inefficient. We set out to ease the challenges with RAG search, that is when we came across DataStax and we were able to optimize LightRAG further for our production ready use cases by leveraging vector search capabilities of AstraDB together with the workflow mapping of Langflow for our internal stakeholders and customers.

What do you like best about the product?

DataStax made it incredibly easy to build and scale our AI agent with Langflow. AstraDB’s serverless architecture meant we didn’t have to worry about provisioning infrastructure, and the integration with vector search made RAG workflows lightning-fast. We especially loved how well AstraDB plugged into Langflow – it felt like building with building blocks. The documentation is clean, the UI is intuitive, and support was responsive and helpful whenever we had questions. If you’re building anything AI-driven with persistent memory, AstraDB is a no-brainer.

What do you dislike about the product?

While AstraDB is incredibly powerful, the learning curve can be a bit steep for first-time users — especially around schema design and understanding CQL for more complex queries. We also noticed that some SDKs or tooling examples lag behind the latest feature releases, which required digging through docs or GitHub issues. That said, the support team and community are active and helpful when you hit a wall.

What problems is the product solving and how is that benefiting you?

We needed a scalable, low-latency vector database to power our AI agent’s memory and retrieval workflows. DataStax Astra DB gave us exactly that — without the DevOps burden. It helps us manage embeddings efficiently and query them with speed, enabling real-time search and personalized responses inside our Langflow-based LLM app. It’s saved us significant engineering time while allowing us to ship faster and more reliably.

What do you like best about the product?

As a company building and stress-testing RAG pipelines daily, the combination of DataStax Astra DB and Langflow has been a game-changer. DataStax delivers scalable, high-speed vector search with excellent integration via the Astra DB and LangChain ecosystem—perfect for low-latency, high-volume workloads. Langflow, on the other hand, makes LLM orchestration visual and intuitive. It accelerates prototyping while still being customizable enough for production-grade workflows. Together, they reduce dev time significantly and let me focus more on refining prompts and grounding logic, rather than infrastructure.

Pros:
Astra DB’s fast vector search and native LangChain support
Langflow’s drag-and-drop interface for rapid experimentation
Easy integration with OpenAI, Cohere, and other providers
Scales well without overcomplicating the stack

What do you dislike about the product?

Langflow is Currently in Preview which might limit deployment to Production Environments

What problems is the product solving and how is that benefiting you?

Helping us build and iterate RAG Workflows at scale with simple UI and Testing

What do you like best about the product?

DataStax offers high performance, scalability, and enterprise-grade features built on Apache Cassandra, making it ideal for handling large-scale, real-time data.

What do you dislike about the product?

Setting up and managing it can be complex, especially for beginners, and pricing may be high for smaller teams.

What problems is the product solving and how is that benefiting you?

DataStax makes it easy to handle big data and ensures high availability with minimal downtime. It helps us scale smoothly and manage data across multiple locations.

What do you like best about the product?

Scalability of architecture
Less downtime

What do you dislike about the product?

Nothing so far,
Still observing the system

What problems is the product solving and how is that benefiting you?

Downtime reduction